BBVA / UMALLinks
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians
☆20Updated 6 years ago
Alternatives and similar repositories for UMAL
Users that are interested in UMAL are comparing it to the libraries listed below
Sorting:
- Exploring how to to deal with uncertain inputs with gaussian process regression models.☆27Updated 4 years ago
- Multi-Output Gaussian Process Toolkit☆183Updated 8 months ago
- ☆156Updated 3 years ago
- Bayesian Learning and Neural Networks (jupyter book sources)☆57Updated 2 years ago
- Bayesian neural networks via MCMC: tutorial☆61Updated last year
- Streaming sparse Gaussian process approximations☆69Updated 3 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆128Updated last year
- A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)☆165Updated 4 years ago
- GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data☆49Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Python package 'dgpsi' for deep and linked Gaussian process emulations☆28Updated 2 months ago
- Bayesian Committee Machines in Python with GPy and multiprocessing☆20Updated 6 years ago
- A framework for composing Neural Processes in Python☆89Updated last year
- Stochastic variational heteroscedastic Gaussian process☆15Updated 6 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆67Updated last year
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.☆39Updated 3 years ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆64Updated 4 years ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 4 years ago
- A Bayesian optimization toolbox built on TensorFlow☆248Updated 3 weeks ago
- Minimalist version of probml/rebayes☆10Updated 4 months ago
- Conformalized Quantile Regression☆302Updated last week
- Literature and light wrappers for gaussian process models.☆47Updated 4 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated 2 years ago
- Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning☆215Updated this week
- ☆48Updated last year
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆228Updated last year
- A tutorial about Gaussian process regression☆193Updated 5 years ago
- Machine Learning and the Physical World module☆29Updated 2 months ago
- Source Code for 'Bayesian Optimization' by Peng Liu☆30Updated 2 years ago